In the final step of our method, the mitosis candidates discovered in the previous step were verified using a classifier. Here, we trained an Efficient-Net-B7 [1]} classifier to distinguish between mitoses and mimickers. To train the classifier we extracted mitosis and mimicker patches (\(96\times 96\)  pixels) based on the annotations provided by the challenge organizers. Again, to deal with the problem of class imbalance, we incorporated the on-the-fly under-sampling technique.
